The invention relates to carrying out research on a road vehicle in relation to its environment. A road vehicle, such as a passenger car or a lorry, is almost always in an environment in which there are also other road vehicles. Consideration may be given, for example, to driving in queues or the like. As is known, in that context there are increasing problems relating to the ever growing demand for mobility, the increasing number of vehicles and the comparative lack of road capacity. The resulting delays in the transportation of people and goods cause considerable economic losses and lead to many other undesirable effects, such as road rage, late attendance at appointments and the like.
On the other hand, local infrastructure and environmental requirements restrict the growth of the road network. For these reasons, there is a need to search for more efficient and more intensive utilization of the existing road network. In this context, consideration is given to increasing the capacity of this network by enabling the vehicles to flow more uniformly and at shorter distances from one another, for example in columns or convoys (“platooning”).
Improved flow of this nature can only safely be achieved if the vehicles and the road network are linked by means of intelligent systems. Such systems may comprise computers on board the vehicles, actuators for regulating speed and direction, sensors and possibly communications systems.
Examples of such systems which may be mentioned include “active cruise control”, that is to say a system in which not only a specific, preset vehicle speed, but also a specific distance to a vehicle in front can be maintained. With a system of this type, it is possible to use a radar to measure the distance at which a vehicle is following a vehicle ahead, and this distance can be used to take over responsibility for the driver's function by means of automatic intervention in the actuation of brake and accelerator.
When developing intelligent systems for road vehicles, an important role is ascribed to simulation techniques. Such systems and vehicles, however, need to be extensively tested and analysed before safe and reliable implementation can be achieved in practice.
There have to date been various approaches in this respect. Firstly, it can be attempted to use computer simulation to carry out an analysis on the basis of a reality model. A simulation of this nature is inexpensive, but the reliability of the results is highly dependent on the model used. Moreover, significance can only be attached to such a model after extensive validation. However, great care is required when developing new systems, since unknown phenomena (such as non-linearities, insufficient degrees of freedom) can have a serious effect on the reliability of the model.
A second possibility for testing intelligent systems relates to the use of complete prototypes. The advantage of this is that all the components to be researched and also all physical effects are present. However, the high costs and complexity represent drawbacks. The reproducibility of such tests with complete prototypes also presents a problem. The tests are often disrupted by uncontrollable boundary conditions, such as wind, rain, state of the road surface and the like. Inadequacies in the prototype itself may also lead to problems. Furthermore, the risks associated with such tests are relatively great. For example, in tests which relate to short distances between the vehicles, collisions may occur, which cause danger to the test personnel and may lead to damage to the expensive prototypes.
According to a third possibility, tests on components or subsystems may be carried out on a test stand. However, a problem with stationary systems of this type is that it is not possible to adequately simulate the operation of sensors. After all, the correct operation of sensors and the associated control operations can only be investigated if relative movements are carried out. The latter is impossible with a stationary system of this type.